Custom Software Research Articles

TransKinect: a computer vision and machine learning clinical decision support system for automatic independent wheelchair transfer technique assessment

Background Physical and occupational therapists provide routine care for manual wheelchair users and are responsible for training and assessing the quality of transfers. These transfers can produce large loads on the upper extremity joints if improper sitting-pivot-technique is used. Methods to assess quality of transfers include the Transfer Assessment Instrument, a clinically validated tool derived from quantitative biomechanical features; however, adoption of this tool is low due to the complex usage requirements and speed of typical transfers. Objective The objective of this study is to develop and validate a computer vison and machine learning solution to better implement the Transfer Assessment Instrument in clinical settings. Methods The prototype system, TransKinect, consists of an infrared depth sensor and a custom software application; usability testing was carried out with fifteen therapists who performed two transfer assessments with the TransKinect. Proficiency in using features, usability, acceptability and satisfaction were analysed with validated surveys and themes were extracted from the qualitative feedback. Results The therapists were able to successfully complete the transfer quality assessments with 86.7 ± 5.4% proficiency. Total scores for System Usability Scale (77.6 ± 14.7%) and Questionnaire for User Interface Satisfaction (83.5 ± 8.7%) indicated that the system was usable and satisfactory. Qualitative feedback indicated that TransKinect was user-friendly, easy to learn, and had high potential. Discussion The results support TransKinect as a potential clinical decision support system for therapists for the comprehensive assessment of independent transfer technique. Future research is needed to investigate the utility and acceptance of TransKinect in real clinical environments. Implications for Rehabilitation Machine learning and computer vision can be used to analyze transfer technique TransKinect is a usable and user-friendly means for therapists to automate analysis Summary reports and videos of transfers show high potential for clinical use Adoption of TransKinect can increase quality of care for manual wheelchair users

EMOKINE: A software package and computational framework for scaling up the creation of highly controlled emotional full-body movement datasets

EMOKINE is a software package and dataset creation suite for emotional full-body movement research in experimental psychology, affective neuroscience, and computer vision. A computational framework, comprehensive instructions, a pilot dataset, observer ratings, and kinematic feature extraction code are provided to facilitate future dataset creations at scale. In addition, the EMOKINE framework outlines how complex sequences of movements may advance emotion research. Traditionally, often emotional-‘action’-based stimuli are used in such research, like hand-waving or walking motions. Here instead, a pilot dataset is provided with short dance choreographies, repeated several times by a dancer who expressed different emotional intentions at each repetition: anger, contentment, fear, joy, neutrality, and sadness. The dataset was simultaneously filmed professionally, and recorded using XSENS® motion capture technology (17 sensors, 240 frames/second). Thirty-two statistics from 12 kinematic features were extracted offline, for the first time in one single dataset: speed, acceleration, angular speed, angular acceleration, limb contraction, distance to center of mass, quantity of motion, dimensionless jerk (integral), head angle (with regards to vertical axis and to back), and space (convex hull 2D and 3D). Average, median absolute deviation (MAD), and maximum value were computed as applicable. The EMOKINE software is appliable to other motion-capture systems and is openly available on the Zenodo Repository. Releases on GitHub include: (i) the code to extract the 32 statistics, (ii) a rigging plugin for Python for MVNX file-conversion to Blender format (MVNX=output file XSENS® system), and (iii) a Python-script-powered custom software to assist with blurring faces; latter two under GPLv3 licenses.

Cost-Efficient Oceanographic Instrument with Microfabricated Sensors for Measuring Conductivity, Temperature and Depth of Seawater.

The design, fabrication and characterization of a cost-efficient oceanographic instrument with microfabricated sensors for measuring conductivity, temperature and depth of seawater are presented. Conductivity and temperature sensors were fabricated using MEMS technology, which allows for customized small footprints and low production costs. Dedicated electronics for reading, processing and storing acquired sensor data are described. The developed instrument enables the measurement of seawater conductivity in a range from 4 mS/cm to 70 mS/cm. The conductivity measurement is temperature-compensated in the range from 2 °C to 40 °C, with an accuracy of ±0.1 mS/cm. The temperature sensor's stability is 0.025 °C. The depth/pressure measurement range is up to 2000 m/200 bar, with a resolution of 0.1 bar. Temperature and conductivity sensor performance was assessed using laboratory equipment and designed electronics. The conductivity sensor was temperature-compensated to 0.01 mS/cm. The conductivity sensor electrode corrosion effect is presented below and was eliminated through adaptation of a signal acquisition circuit. Custom software was developed for monitoring critical conductivity sensor parameters (currents, voltages). A variation of 0.4% between cell conductance currents and voltages was established as a criterion for stable conductivity sensor operation.

NerveTracker: a Python-based software toolkit for visualizing and tracking groups of nerve fibers in serial block-face microscopy with ultraviolet surface excitation images.

Information about the spatial organization of fibers within a nerve is crucial to our understanding of nerve anatomy and its response to neuromodulation therapies. A serial block-face microscopy method [three-dimensional microscopy with ultraviolet surface excitation (3D-MUSE)] has been developed to image nerves over extended depths ex vivo. To routinely visualize and track nerve fibers in these datasets, a dedicated and customizable software tool is required. Our objective was to develop custom software that includes image processing and visualization methods to perform microscopic tractography along the length of a peripheral nerve sample. We modified common computer vision algorithms (optic flow and structure tensor) to track groups of peripheral nerve fibers along the length of the nerve. Interactive streamline visualization and manual editing tools are provided. Optionally, deep learning segmentation of fascicles (fiber bundles) can be applied to constrain the tracts from inadvertently crossing into the epineurium. As an example, we performed tractography on vagus and tibial nerve datasets and assessed accuracy by comparing the resulting nerve tracts with segmentations of fascicles as they split and merge with each other in the nerve sample stack. We found that a normalized Dice overlap ( ) metric had a mean value above 0.75 across several millimeters along the nerve. We also found that the tractograms were robust to changes in certain image properties (e.g., downsampling in-plane and out-of-plane), which resulted in only a 2% to 9% change to the mean values. In a vagus nerve sample, tractography allowed us to readily identify that subsets of fibers from four distinct fascicles merge into a single fascicle as we move along the nerve's length. Overall, we demonstrated the feasibility of performing automated microscopic tractography on 3D-MUSE datasets of peripheral nerves. The software should be applicable to other imaging approaches. The code is available at https://github.com/ckolluru/NerveTracker.

Continuous Assessment of Active-Duty Army Special Operations and Reconnaissance Marines Using Digital Devices and Custom Software: The Digital Comprehensive Operator Readiness Assessment (DcORA) Study.

Continuous exposure to extreme and chronic stress from uncontrollable events has been linked to increased psychological and physiological reactivity. Prolonged, frequent deployments may test coping skills over time, ultimately rendering Servicemembers vulnerable to mental health problems and suicide. This study develops a methodology for accurately collecting holistic health measures from Servicemembers using digital tools, including custom-built phone software and body-worn sensors. The secure research platform and mobile app continuously collect multiple health measures and, after data analysis, deliver continuously updated summary data back to the Servicemember. This system provides novel insights into the relationships between the measures while helping individuals track their progress toward self-established goals. Participants were given an iPhone (including the study app) and an Apple Watch. Participants tracked their data for more than 6 months and responded to baseline, daily, and weekly questions and assessments. Physiologic, psychologic, and cognitive assessment data across the Preservation of the Force and Family program (POTFF) domains were collected, displayed to the individual, and analyzed in aggregate. When coupled with custom-built software, this hardware can be elevated from a fitness tracker to a user-facing health monitoring, educational, and delivery system. This wearable system measured vital factors associated with the health and human performance of Servicemembers. In real-time, it engaged Servicemembers in health and human performance optimization practices to achieve a goal of prevention of physical or mental injury.

Hardware and software solutions for implementing nanospray desorption electrospray ionization (nano-DESI) sources on commercial mass spectrometers.

Nanospray desorption electrospray ionization (nano-DESI) is an ambient ionization mass spectrometry imaging (MSI) approach that enables spatial mapping ofbiological and environmental samples with high spatial resolution and throughput. Because nano-DESI has not yet been commercialized, researchers develop their own sources and interface them with different commercial mass spectrometers. Previously, several protocols focusing on the fabrication of nano-DESI probes have been reported. In this tutorial, we discuss different hardware requirements for coupling the nano-DESI source to commercial mass spectrometers, such as the safety interlock, inlet extension, and contact closure. In addition, we describe the structure of our custom software for controlling the nano-DESI MSI platform and provide detailed instructions for its usage. With this tutorial, interested researchers should be able to implement nano-DESI experiments in their labs.

Features of the operation of the training stand “Electric vehicle motor” in determining the operation characteristics of electric transport

In the modern world, the problem of the ecological state of our planet is acute. The environmental situation depends on many factors, these include both natural phenomena and human actions. One solution to this problem is to replace traditional internal combustion engines with more environmentally friendly electric vehicles.THE PURPOSE. The objective of this study is to analyze the internal structure of an electric vehicle, based on the training stand “Electric Vehicle Motor”, as well as to study the functions of this device, located at the Kazan State Energy University.METHODS. The authors of the article processed and analyzed the capabilities of modern laboratory equipment that simulates the operation of a particular component of an electric vehicle.RESULTS. The technology of the laboratory bench operating the electric vehicle, together with the DVT Customer software, allows for full control of the electric motor, as well as monitoring and changing a large number of parameters that affect the operation of the entire device as a whole.CONCLUSION. Since electric vehicles are gaining more and more popularity every year, the demand for people capable of diagnosing, repairing, and even improving existing ones and developing new components and assemblies in the field of electric vehicles is growing significantly. Using the “Electric Vehicle Motor” stand for teaching technical subjects and conducting research work can serve as a good basis for the formation of a general knowledge base about electric transport, its structure, the operating principle of all the main elements, monitoring and diagnostics of an electric vehicle.

Collective hydrogen stand-alone renewable energy systems for buildings in Spain. Towards the self-sufficiency

The article examines the feasibility of implementing standalone hydrogen-based renewable energy systems in Spanish residential buildings, specifically analyzing the optimization of a solar-battery and solar-hydrogen system for a building with 20 dwellings in Spain. The study initially assesses two standalone setups: solar-battery and solar-hydrogen. Subsequently, it explores scenarios where these systems are connected to the grid to only generate and sell surplus energy. A scenario involving grid connection for self-consumption without storage serves as a benchmark for comparison. All system optimizations are designed to meet energy demands without interruptions while minimizing costs, as determined by a techno-economic analysis. The systems are sized using custom software that incorporates an energy management system and employs the Jaya algorithm for optimization. The findings indicate that selling surplus energy can be economically competitive and enhance the efficiency of grid-connected self-consumption systems, representing the study's main innovation. The conclusion highlights the economic and technical potential of an autonomous hybrid energy system that includes hydrogen, with the significant remaining challenge being the development of a regulatory framework to support its technical feasibility in Spain.

Anterior cruciate ligament injury and age affect knee cartilage T2 but not thickness

ObjectiveTo investigate the effect of unilateral anterior cruciate ligament (ACL) injury on cartilage thickness and composition, specifically laminar transverse relaxation time (T2) by magnetic resonance imaging (MRI), in younger and older participants and to compare within-person side differences in these parameters between ACL-injured and healthy controls. DesignQuantitative double-echo steady-state (qDESS) 3 Tesla MRI-sequences were acquired in both knees of 85 participants in four groups: 20–30 years: healthy, HEA20–30, n=24; ACL-injured, ACL20–30, n=23; 40–60 years: healthy, HEA40–60, n=24; ACL-injured, ACL40–60, n=14 (ACL injury 2–10 years prior to study inclusion). Weight-bearing femorotibial cartilages were manually segmented; cartilage T2 and thickness were computed using custom software. Mean and side difference in subregional cartilage thickness, superficial and deep cartilage T2 were compared within and between groups using non-parametric statistics. ResultsCartilage thickness did not differ within or between groups. Only the side difference in medial femorotibial cartilage thickness was greater in ACL20–30 than in HEA20–30. Deep zone T2 was longer in the ACL-injured than in the contralateral uninjured knees and than in healthy controls, especially in the lateral compartment. Most ACL-injured participants had side differences in femorotibial deep zone T2 above the threshold derived from controls. ConclusionIn the ACL-injured knee, early compositional differences in femorotibial cartilage (T2) appear to occur in the deep zone and precede cartilage thickness loss. These results suggest that monitoring laminar T2 after ACL injury may be useful in the diagnosing and monitoring early articular cartilage changes.

3D printing traceability in healthcare using 3Diamond software

Background3D printing is one of the fastest-growing technologies in medicine, but it is essential to have a system for 3D printing documentation that is accessible for not only clinical engineers and surgeons, but also quality managers and data-privacy officers in hospitals. Dedicated software such as product lifecycle management (PLM) software could enable comprehensive management and traceability of all data relevant to 3D printing tasks in a hospital and would highly beneficial. Therefore, customizable software called 3Diamond was developed for 3D printing in medicine. MethodsThe software development process involved several stages, including setting specifications based on end-user requirements, design, implementation, and testing. In order to ensure the software's long-term success and smooth operation, critical phases were also considered, such as deployment and maintenance. ResultsThe developed software provides immediate and complete traceability of all preparations and controls, as well as management of reports, orders, stock, and post-operative follow-up of tasks related to 3D printing in a hospital. Based on user requirements, software testing is provided automatically with each release. The software was implemented in a natural clinical environment with a developed 3D printing center. ConclusionAlthough 3D printing has potential for innovation in the medical profession, it is nevertheless subject to regulations. Even though there are exemptions for patient-specific products, the effects of their local legal implementations related to 3D printing cannot be fully overseen. To this end, 3Diamond provides a robust system for 3D printing documentation that is accessible to different personnel in hospitals.

Continuous remote monitoring of performance status in patients with NSCLC through fitness tracker–derived life-log data.

1568 Background: Traditional methods for assessing the performance status of cancer patients often rely on clinical evaluations and patient-reported histories. This study utilizes life-log data derived from fitness trackers (FTs) in patients with non-small cell lung cancer (NSCLC) to offer a comprehensive and dynamic perspective on performance status throughout their treatment. Methods: Patients with NSCLC scheduled for a minimum of 12 weeks of treatment were enrolled. Custom software facilitated the remote collection of life-log data from participants' FTs (Fitbit Inspire 3), encompassing step count, calories burned, heart rate, sleep patterns, etc. Quality of life surveys assessing patient-reported outcomes (PROs) were completed during regular visits (every 3 weeks) and unscheduled visits (USV), in addition to collecting clinical data such as laboratory parameters and body composition metrics. An end-of-monitoring survey assessed participants' familiarity with this monitoring approach. The study aimed to correlate FT data with clinical parameters and identify patterns predictive of treatment related USVs. Results: Of the 98 enrolled patients, 69 patients (70.4%) completed the 12-week follow-up. The cohort predominantly consisted of older adults (≥65 years) (55.1%) and patients in palliative care (75.5%), with most undergoing cytotoxic chemotherapy (66.3%) and some receiving oral agents (20%). FT-based remote monitoring revealed that older patients had a comparable 12-week completion rate to younger patients. (69.2% vs. 76.2%, P=0.604). Analysis of life-log data from three days before a visit (D-3) to the visit day (D0) showed significant reductions in average step counts ( P=0.022) and walking distance ( P=0.021) for USVs compared to regular visits, while resting heart rate (HR) showed a significant increase for USVs ( P=0.049). PRO-based PROMIS physical function scores and EQ-5D-3L scores showed a significant correlation with both D-3 to D0 acquired resting HR ( P<0.001, P=0.002) and average step counts ( P=0.011, P=0.013), respectively. End of monitoring survey was done from 72 participants indicating high satisfaction and familiarity with the FT-based remote monitoring system, median score of 90 out of 100. Conclusions: FT-derived life-log data effectively captured dynamic performance status in NSCLC patients, correlating with clinical outcomes and PRO. These findings support further research into FT data's predictive value for clinical interventions, underscoring its potential in personalized remote patient management.

Importance of the lumbar paraspinal muscles on the maintenance of global sagittal alignment after lumbar pedicle subtraction osteotomy.

There are limited data about the influence of the lumbar paraspinal muscles on the maintenance of sagittal alignment after pedicle subtraction osteotomy (PSO) and the risk factors for sagittal realignment failure. The authors aimed to investigate the influence of preoperative lumbar paraspinal muscle quality on the postoperative maintenance of sagittal alignment after lumbar PSO. Patients who underwent lumbar PSO with preoperative lumbar MRI and pre- and postoperative whole-spine radiography in the standing position were included. Spinopelvic measurements included pelvic incidence, sacral slope, pelvic tilt, L1-S1 lordosis, T4-12 thoracic kyphosis, spinosacral angle, C7-S1 sagittal vertical axis (SVA), T1 pelvic angle, and mismatch between pelvic incidence and L1-S1 lordosis. Validated custom software was used to calculate the percent fat infiltration (FI) of the psoas major, as well as the erector spinae and multifidus (MF). A multivariable linear mixed model was applied to further examine the association between MF FI and the postoperative progression of SVA over time, accounting for repeated measures over time that were adjusted for age, sex, BMI, and length of follow-up. Seventy-seven patients were recruited. The authors' results demonstrated significant correlations between MF FI and the maintenance of corrected sagittal alignment after PSO. After adjustment for the aforementioned parameters, the model showed that the MF FI was significantly associated with the postoperative progression of positive SVA over time. A 1% increase from the preoperatively assessed total MF FI was correlated with an increase of 0.92 mm in SVA postoperatively (95% CI 0.42-1.41, p < 0.0001). This study included a large patient cohort with midterm follow-up after PSO and emphasized the importance of the lumbar paraspinal muscles in the maintenance of sagittal alignment correction. Surgeons should assess the quality of the MF preoperatively in patients undergoing PSO to identify patients with severe FI, as they may be at higher risk for sagittal decompensation.

Predictive Software Engineering: Empowering Business Success with Tailored Software Solutions

This paper explores the seven core principles of the Predictive Software Engineering (PSE) framework. These principles are designed to empower custom software development companies to deliver transparent and reliable solutions, all while adhering to predetermined budgets. The paper delves into each of the seven principles: Meaningful Customer Care, Transparent End-to-End Control, Proven Productivity, Efficient Distributed Teams, Disciplined Agile Delivery Process, Measurable Quality Management and Technical Debt Reduction, and Sound Human Development.

Effects of induced arterial hypertension for vasospasm on unruptured and unsecured cerebral aneurysms (growth and rupture). A retrospective case-control study

ObjectivesUnruptured cerebral aneurysms (UCAs) often coexist with the ruptured one but are typically left unsecured during the weeks following aneurysmal subarachnoid hemorrhage (aSAH). We compared the rate of UCAs rupture or volume growth (≥5 mm3) between patients exposed to induced arterial hypertension (iHTN) for vasospasm and those not exposed (control group). Materials and MethodsFrom 2013 to 2021, we retrospectively included consecutive adult patients with aSAH who had ≥1 UCA. Custom software for digital subtraction angiography (DSA) image analysis characterized UCAs volume, going beyond merely considering UCAs long axis. ResultsWe analyzed 118 patients (180 UCAs): 45 in the iHTN group (64 UCAs) and 73 in the control group (116 UCAs). Systolic blood pressure in the iHTN group was significantly higher than in the control group for several days after aSAH. During the 107 day-monitoring period [interquartile range(IQR):92;128], no UCA rupture occurred in either group. UCA volume analysis was performed in 44 patients (60 UCAs): none of the UCAs in the iHTN group and 3 out of 42 (7%) in the control group had a >5 mm3 volume growth (p=0.55). Other morphologic parameters did not exhibit any variations that might indicate an increased risk of rupture in the iHTN group compared to the control group. ConclusioniHTN did not increase the risk of rupture or volume growth of UCAs within several weeks following aSAH. These reassuring results encourage not to refrain, because of the existence of UCAs, from iHTN as an option to prevent cerebral infarction during cerebral vasospasm.

Design, Fabrication, and Validation of a Portable Perturbation Treadmill for Balance Recovery Research.

Trips and falls are a major concern for older adults. The resulting injury and loss of mobility can have a significant impact on quality of life. An emerging field of study, known as Perturbation Training, has been shown to reduce injury rates associated with trips and falls in older adults. Treadmills traditionally used for Perturbation Training are large, expensive, and immobile, forcing users to travel long distances to receive care. A portable treadmill would serve a larger portion of the at-risk population than current methods. We developed a portable, low-cost, twin-belt perturbation treadmill capable of high-intensity Perturbation Training. Belt speeds are controlled by a custom mechanical and software interface, allowing operators with no programming experience to control the device. The treadmill can accommodate users up to 118 kg and provides a maximum acceleration and speed of 12 m/s2 and 3.3 m/s, respectively, under full load. The total weight is 180 kg, and the treadmill can be moved like a wheelbarrow, with handles in the back and wheels in the front. The prototype was validated with mechanical and human participant testing, showing it as a viable device for Perturbation Training. In this paper, we will go over the design, fabrication, and validation processes used to create the Portable Perturbation Treadmill.

The time course of the rate of speaker transitions in conversation

Using over 500 hours of recorded conversations from the CallHome and CallFriend corpora (MacWhinney &amp; Wagner 2010), this study analyzes conversations to measure gaps and overlaps in speaker transitions. It builds on previous work in (1) measuring speaker transitions by using custom software that measures single speaker segments based solely on acoustic evidence, without the need for a transcription or manual configuration, and (2) by breaking down the conversations and evaluating the transition rates minute by minute. Across the seven different languages studied, a pattern emerges in the rate of speaker transitions over the course of time. The number of transitions is highest in the first minute and gradually decreases before coming to a more consistent rate. This pattern exists in each of the languages studied, despite language-specific differences in turn-taking behavior. The cross-linguistic consistency of the decrease in the transition rate over the first several minutes of a conversation suggests that accommodation may be occurring as speakers negotiate the cadence of their interchanges with each other.

The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.

Evaluation of standard echocardiographic examination with artificial intelligence may help in the diagnosis of myocardial viability and function recovery after acute coronary syndrome. Sixty-one consecutive patients with acute coronary syndrome were enrolled in the present study (43 men, mean age 61 ± 9 years). All patients underwent percutaneous coronary intervention (PCI). 533 segments of the heart echo images were used. After 12 ± 1 months of follow-up, patients had an echocardiographic evaluation. After PCI each patient underwent cardiac magnetic resonance (CMR) with late enhancement and low-dose dobutamine echocardiographic examination. For texture analysis, custom software was used (MaZda 5.20, Institute of Electronics).Linear and non-linear (neural network) discriminative analyses were performed to identify the optimal analytic method correlating with CMR regarding the necrosis extent and viability prediction after follow-up. Texture parameters were analyzed using machine learning techniques: Artificial Neural Networks, Namely Multilayer Perceptron, Nonlinear Discriminant Analysis, Support Vector Machine, and Adaboost algorithm. The mean concordance between the CMR definition of viability and three classification models in Artificial Neural Networks varied from 42% to 76%. Echo-based detection of non-viable tissue was more sensitive in the segments with the highest relative transmural scar thickness: 51-75% and 76-99%. The best results have been obtained for images with contrast for red and grey components (74% of proper classification). In dobutamine echocardiography, the results of appropriate prediction were 67% for monochromatic images. Detection and semi-quantification of scar transmurality are feasible in echocardiographic images analyzed with artificial intelligence. Selected analytic methods yielded similar accuracy, and contrast enhancement contributed to the prediction accuracy of myocardial viability after myocardial infarction in 12 months of follow-up.

Design of a handheld and portable fluorescence imaging system for quantitative detection of pregnancy-specific biomarkers in cattle.

Reproductive management significantly impacts dairy farm productivity, necessitating accurate timely pregnancy detection in cattle. This paper presents a novel handheld and portable fluorescence imaging system designed for quantitative assessment of pregnancy-specific biomarkers, addressing the limitations of current detection methods. The objective was to develop a cost-effective, at-farm solution for detecting pregnancy-specific protein B (PSPB) in bovine plasma samples. The system integrates an imaging module and a custom software application, enabling image capture, data processing, and PSPB concentration determination. Calibration utilizing known PSPB concentrations achieved a 0.6ng/mL limit of detection. Validation encompassed a comparison with a standard ELISA method using 100 bovine plasma samples; minimal bias and good agreement were observed within the linear range of the calibration curve for both methods. The system offers portability, user-friendliness, and potential for multiplex detection, promising real-time, at-farm reproductive management. This study demonstrates the successful development and validation of a portable fluorescence imaging system, offering an efficient and accurate approach to detecting pregnancy-specific biomarkers in cattle. Its implications extend to improving dairy farm productivity by enabling timely and reliable reproductive management practices.

Comparing novel smartphone pose estimation frameworks with the Kinect V2 for knee tracking during athletic stress tests.

To compare the accuracy of the Microsoft Kinect V2 with novel pose estimation frameworks, in assessing knee kinematics during athletic stress tests, for fast and portable risk assessment of anterior cruciate ligament (ACL) injury. We captured 254 varsity athletes, using the Kinect V2 and a smartphone application utilizing Google's MediaPipe framework. The devices were placed as close as possible and used to capture a person, facing the cameras, performing one of three athletic stress tests at a distance of 2.5ms. Custom software translated the results from both frameworks to the same format. We then extracted relevant knee angles at key moments of the jump and compared them, using the Kinect V2 as the ground truth. The results show relatively small angle differences between the two solutions in the coronal plane and moderate angle differences on the sagittal plane. Overall, the MediaPipe framework results seem to underestimate both knee valgus angles and knee sagittal angles compared to the Kinect V2. This preliminary study demonstrates the potential for Google's MediaPipe framework to be used for calculating lower limb kinematics during athletic stress test motions, which can run on most modern smartphones, as it produces similar results to the Kinect V2. A smartphone application similar to the one developed could potentially be used for low cost and widespread ACL injury prevention.

QTL for the Kinematic Traits That Define the Arabidopsis Root Elongation Zone and Their Relationship to Gravitropism.

Cell expansion in a discrete region called the elongation zone drives root elongation. Analyzing time lapse images can quantify the expansion in kinematic terms as if it were fluid flow. We used horizontal microscopes to collect images from which custom software extracted the length of the elongation zone, the peak relative elemental growth rate (REGR) within it, the axial position of the REGR peak, and the root elongation rate. Automation enabled these kinematic traits to be measured in 1575 Arabidopsis seedlings representing 162 recombinant inbred lines (RILs) derived from a cross of Cvi and Ler ecotypes. We mapped ten quantitative trait loci (QTL), affecting the four kinematic traits. Three QTL affected two or more traits in these vertically oriented seedlings. We compared this genetic architecture with that previously determined for gravitropism using the same RIL population. The major QTL peaks for the kinematic traits did not overlap with the gravitropism QTL. Furthermore, no single kinematic trait correlated with quantitative descriptors of the gravitropism response curve across this population. In addition to mapping QTL for growth zone traits, this study showed that the size and shape of the elongation zone may vary widely without affecting the differential growth induced by gravity.